fractal organizations part i – complexity

49
FRACTAL ORGANIZATIONS Part I - COMPLEXITY FATMA ÇINAR, Mba KUTLU MERİH, Phd

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Page 1: Fractal Organizations Part I – Complexity

FRACTAL ORGANIZATIONS

Part I - COMPLEXITY

FATMA CcedilINAR Mba

KUTLU MERİH Phd

Systems as Complex Beings

Complex Systems characteristics

Complex Adaptation of Systems CAS

Organizations as Complex Adaptive Systems

Edge of Chaos

Self Orgnization amp Emergence

Part I Fundamental Concepts of Complexity Theory

Presentation Outline

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of Object Oriented Approach

Description of the Objects

Organization as a Complex of Objects

Object Oriented Business Modelling

Organizational Agents

Sycamore Tree Diagram of Organizations

Organizational Sycamore Tree Agents

The CORTEX

(CBBC) ndash Complexity Business Balance Cardrdquo

Presentation Outline

Part II Object Based Complexity Approach

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

In this study with two parts we propose a new modelling technique based on Object BasedComplexity Modelling of the of the organizations

First we describe the basic aspects of Complexity approach Part I

Then we redefine the concept of complexity Andapplication to organizations by the aid of laquoobject orientationraquo concept of software technology Part II

Then we apply this new approach to set up a new management paradigm as Sycamore Tree Diagramand Complexity

IntroductionO

bje

ct-

Ba

sed

Co

mp

lex

ity

Mo

deli

ng

Ap

pli

ca

tio

n

Te

ch

niq

ues

Why Complexity Based Approach

For contemporary organizations

analytical and quantitative modeling

techniques are not sufficient for

modeling of the complex structured

corporate management activities

Mathematical and statistical methods

lack of performance to express the

impact of intangible factors

That makes mandatory to use new

models that are based on organic

thinking Informatics and control theory

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

Organizations

All technical and business practices applied in

contemporary organizations fails to simplify the

complexity of situation

They also far from to cover structural relations

which are necessary for a good model

TQM is a delicate Japanese flower

which has no chance to live on rocky

American mountains

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

OrganizationsDead Diagrams of the Analytical World

Designing stylish organigrams come before to define

the problems correctly and fail to represent the

relations and analyse them correctly

Representing the multi-dimension organizations on

the paper with two dimension do more harm than its

benefits

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Why Fractal Nesting

Relations and time are the intangible assets of

the business to be managed

They have a metric on their own which we can

not measure but we know that they affect

business performance

This metric can be changed in the process but

we are unable to express it as mathematical

and arithmetical concepts

For This Reason We Apply the Fractal Concept

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Nowadays we are able to pick up

business processes within few days with

the internet and logistics support

That means that the performance metrics

has changed at the same time also

increased the level of performance

Why Fractal Nesting

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 2: Fractal Organizations Part I – Complexity

Systems as Complex Beings

Complex Systems characteristics

Complex Adaptation of Systems CAS

Organizations as Complex Adaptive Systems

Edge of Chaos

Self Orgnization amp Emergence

Part I Fundamental Concepts of Complexity Theory

Presentation Outline

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of Object Oriented Approach

Description of the Objects

Organization as a Complex of Objects

Object Oriented Business Modelling

Organizational Agents

Sycamore Tree Diagram of Organizations

Organizational Sycamore Tree Agents

The CORTEX

(CBBC) ndash Complexity Business Balance Cardrdquo

Presentation Outline

Part II Object Based Complexity Approach

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

In this study with two parts we propose a new modelling technique based on Object BasedComplexity Modelling of the of the organizations

First we describe the basic aspects of Complexity approach Part I

Then we redefine the concept of complexity Andapplication to organizations by the aid of laquoobject orientationraquo concept of software technology Part II

Then we apply this new approach to set up a new management paradigm as Sycamore Tree Diagramand Complexity

IntroductionO

bje

ct-

Ba

sed

Co

mp

lex

ity

Mo

deli

ng

Ap

pli

ca

tio

n

Te

ch

niq

ues

Why Complexity Based Approach

For contemporary organizations

analytical and quantitative modeling

techniques are not sufficient for

modeling of the complex structured

corporate management activities

Mathematical and statistical methods

lack of performance to express the

impact of intangible factors

That makes mandatory to use new

models that are based on organic

thinking Informatics and control theory

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

Organizations

All technical and business practices applied in

contemporary organizations fails to simplify the

complexity of situation

They also far from to cover structural relations

which are necessary for a good model

TQM is a delicate Japanese flower

which has no chance to live on rocky

American mountains

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

OrganizationsDead Diagrams of the Analytical World

Designing stylish organigrams come before to define

the problems correctly and fail to represent the

relations and analyse them correctly

Representing the multi-dimension organizations on

the paper with two dimension do more harm than its

benefits

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Why Fractal Nesting

Relations and time are the intangible assets of

the business to be managed

They have a metric on their own which we can

not measure but we know that they affect

business performance

This metric can be changed in the process but

we are unable to express it as mathematical

and arithmetical concepts

For This Reason We Apply the Fractal Concept

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Nowadays we are able to pick up

business processes within few days with

the internet and logistics support

That means that the performance metrics

has changed at the same time also

increased the level of performance

Why Fractal Nesting

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 3: Fractal Organizations Part I – Complexity

The Reasons of Object Oriented Approach

Description of the Objects

Organization as a Complex of Objects

Object Oriented Business Modelling

Organizational Agents

Sycamore Tree Diagram of Organizations

Organizational Sycamore Tree Agents

The CORTEX

(CBBC) ndash Complexity Business Balance Cardrdquo

Presentation Outline

Part II Object Based Complexity Approach

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

In this study with two parts we propose a new modelling technique based on Object BasedComplexity Modelling of the of the organizations

First we describe the basic aspects of Complexity approach Part I

Then we redefine the concept of complexity Andapplication to organizations by the aid of laquoobject orientationraquo concept of software technology Part II

Then we apply this new approach to set up a new management paradigm as Sycamore Tree Diagramand Complexity

IntroductionO

bje

ct-

Ba

sed

Co

mp

lex

ity

Mo

deli

ng

Ap

pli

ca

tio

n

Te

ch

niq

ues

Why Complexity Based Approach

For contemporary organizations

analytical and quantitative modeling

techniques are not sufficient for

modeling of the complex structured

corporate management activities

Mathematical and statistical methods

lack of performance to express the

impact of intangible factors

That makes mandatory to use new

models that are based on organic

thinking Informatics and control theory

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

Organizations

All technical and business practices applied in

contemporary organizations fails to simplify the

complexity of situation

They also far from to cover structural relations

which are necessary for a good model

TQM is a delicate Japanese flower

which has no chance to live on rocky

American mountains

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

OrganizationsDead Diagrams of the Analytical World

Designing stylish organigrams come before to define

the problems correctly and fail to represent the

relations and analyse them correctly

Representing the multi-dimension organizations on

the paper with two dimension do more harm than its

benefits

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Why Fractal Nesting

Relations and time are the intangible assets of

the business to be managed

They have a metric on their own which we can

not measure but we know that they affect

business performance

This metric can be changed in the process but

we are unable to express it as mathematical

and arithmetical concepts

For This Reason We Apply the Fractal Concept

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Nowadays we are able to pick up

business processes within few days with

the internet and logistics support

That means that the performance metrics

has changed at the same time also

increased the level of performance

Why Fractal Nesting

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 4: Fractal Organizations Part I – Complexity

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

In this study with two parts we propose a new modelling technique based on Object BasedComplexity Modelling of the of the organizations

First we describe the basic aspects of Complexity approach Part I

Then we redefine the concept of complexity Andapplication to organizations by the aid of laquoobject orientationraquo concept of software technology Part II

Then we apply this new approach to set up a new management paradigm as Sycamore Tree Diagramand Complexity

IntroductionO

bje

ct-

Ba

sed

Co

mp

lex

ity

Mo

deli

ng

Ap

pli

ca

tio

n

Te

ch

niq

ues

Why Complexity Based Approach

For contemporary organizations

analytical and quantitative modeling

techniques are not sufficient for

modeling of the complex structured

corporate management activities

Mathematical and statistical methods

lack of performance to express the

impact of intangible factors

That makes mandatory to use new

models that are based on organic

thinking Informatics and control theory

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

Organizations

All technical and business practices applied in

contemporary organizations fails to simplify the

complexity of situation

They also far from to cover structural relations

which are necessary for a good model

TQM is a delicate Japanese flower

which has no chance to live on rocky

American mountains

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

OrganizationsDead Diagrams of the Analytical World

Designing stylish organigrams come before to define

the problems correctly and fail to represent the

relations and analyse them correctly

Representing the multi-dimension organizations on

the paper with two dimension do more harm than its

benefits

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Why Fractal Nesting

Relations and time are the intangible assets of

the business to be managed

They have a metric on their own which we can

not measure but we know that they affect

business performance

This metric can be changed in the process but

we are unable to express it as mathematical

and arithmetical concepts

For This Reason We Apply the Fractal Concept

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Nowadays we are able to pick up

business processes within few days with

the internet and logistics support

That means that the performance metrics

has changed at the same time also

increased the level of performance

Why Fractal Nesting

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 5: Fractal Organizations Part I – Complexity

Why Complexity Based Approach

For contemporary organizations

analytical and quantitative modeling

techniques are not sufficient for

modeling of the complex structured

corporate management activities

Mathematical and statistical methods

lack of performance to express the

impact of intangible factors

That makes mandatory to use new

models that are based on organic

thinking Informatics and control theory

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

Organizations

All technical and business practices applied in

contemporary organizations fails to simplify the

complexity of situation

They also far from to cover structural relations

which are necessary for a good model

TQM is a delicate Japanese flower

which has no chance to live on rocky

American mountains

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

OrganizationsDead Diagrams of the Analytical World

Designing stylish organigrams come before to define

the problems correctly and fail to represent the

relations and analyse them correctly

Representing the multi-dimension organizations on

the paper with two dimension do more harm than its

benefits

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Why Fractal Nesting

Relations and time are the intangible assets of

the business to be managed

They have a metric on their own which we can

not measure but we know that they affect

business performance

This metric can be changed in the process but

we are unable to express it as mathematical

and arithmetical concepts

For This Reason We Apply the Fractal Concept

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Nowadays we are able to pick up

business processes within few days with

the internet and logistics support

That means that the performance metrics

has changed at the same time also

increased the level of performance

Why Fractal Nesting

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 6: Fractal Organizations Part I – Complexity

Fundamental Problems of Contemporary

Organizations

All technical and business practices applied in

contemporary organizations fails to simplify the

complexity of situation

They also far from to cover structural relations

which are necessary for a good model

TQM is a delicate Japanese flower

which has no chance to live on rocky

American mountains

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Fundamental Problems of Contemporary

OrganizationsDead Diagrams of the Analytical World

Designing stylish organigrams come before to define

the problems correctly and fail to represent the

relations and analyse them correctly

Representing the multi-dimension organizations on

the paper with two dimension do more harm than its

benefits

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Why Fractal Nesting

Relations and time are the intangible assets of

the business to be managed

They have a metric on their own which we can

not measure but we know that they affect

business performance

This metric can be changed in the process but

we are unable to express it as mathematical

and arithmetical concepts

For This Reason We Apply the Fractal Concept

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Nowadays we are able to pick up

business processes within few days with

the internet and logistics support

That means that the performance metrics

has changed at the same time also

increased the level of performance

Why Fractal Nesting

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 7: Fractal Organizations Part I – Complexity

Fundamental Problems of Contemporary

OrganizationsDead Diagrams of the Analytical World

Designing stylish organigrams come before to define

the problems correctly and fail to represent the

relations and analyse them correctly

Representing the multi-dimension organizations on

the paper with two dimension do more harm than its

benefits

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Why Fractal Nesting

Relations and time are the intangible assets of

the business to be managed

They have a metric on their own which we can

not measure but we know that they affect

business performance

This metric can be changed in the process but

we are unable to express it as mathematical

and arithmetical concepts

For This Reason We Apply the Fractal Concept

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Nowadays we are able to pick up

business processes within few days with

the internet and logistics support

That means that the performance metrics

has changed at the same time also

increased the level of performance

Why Fractal Nesting

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 8: Fractal Organizations Part I – Complexity

Why Fractal Nesting

Relations and time are the intangible assets of

the business to be managed

They have a metric on their own which we can

not measure but we know that they affect

business performance

This metric can be changed in the process but

we are unable to express it as mathematical

and arithmetical concepts

For This Reason We Apply the Fractal Concept

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Nowadays we are able to pick up

business processes within few days with

the internet and logistics support

That means that the performance metrics

has changed at the same time also

increased the level of performance

Why Fractal Nesting

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 9: Fractal Organizations Part I – Complexity

Nowadays we are able to pick up

business processes within few days with

the internet and logistics support

That means that the performance metrics

has changed at the same time also

increased the level of performance

Why Fractal Nesting

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 10: Fractal Organizations Part I – Complexity

The Reasons of the Object Oriented Approach

Conventional analytical models was not able to reflect

the dynamics of the process of functional data but only

the status at a given moment

With the Object -based modeling model always is in

communication with the available mass of data and the

many interventions can be made on-line real-time

The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments

Object -Based Models

are direct

management tools

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 11: Fractal Organizations Part I – Complexity

Until recently the light by which science was working was

only able to illuminate simple linear systems

The advent of the computer and big data warehouses

changed things

It is now possible to look at systems as complex beings

which has strange behaviour patterns

Fundamental Concepts of Complexıty Theory

Systems as Complex Beings

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 12: Fractal Organizations Part I – Complexity

The field is still very new and there is no agreement about terms and

terminology but the following quotes enough to give us a flavour

Complex adaptive systems consist of a number of components or agents that

interact with each other according to sets of rules that require them to examine

and respond to each otherrsquos behaviour in order to improve their behaviour and

thus the behaviour of the system they comprise (Stacey 1996)

A system that is complex in the sense that a great many independent agents

are interacting with each other in a great many ways (Waldrop 1993)

What is a complex system

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 13: Fractal Organizations Part I – Complexity

Complexity Arises Interacting of Simple Components

In a complex system you generally find that the basic components and the basic laws are

quite simple the complexity arises because you have a great many of these simple

components interacting simultaneously

The complex whole may exhibit properties that are not readily explained by understanding its

parts

Because complexity results from the interaction between the components of a system

complexity is manifested at the level of the system itself

To understand the behavior of a complex system we must understand not only the behaviour

of the parts but how they act together to form the whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 14: Fractal Organizations Part I – Complexity

Small set of simple rules

Some approaches have been used to model behaviours in the natural world

One of the pioneers was Craig Reynolds (1987) who modelled flocking

behaviour using a small set of rules

Separation steer to avoid crowding local flockmates

Alignment steer towards the average heading of local flockmates

Cohesion steer to move toward the average position of local flockmates

These three simple rules can change a random assembly of agents into a

cohesive group looking just like a flock of birds or shoal of fish

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 15: Fractal Organizations Part I – Complexity

Complex System Characteristics

In the early days of complex systems theory the emphasis was on large

networks of simple agents with simple interactions

More recently there has been a realisation that smaller networks of complex

agents can show the same kinds of behaviour and can be equally complex

Complex systems have a number of properties some of which are listed

below

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 16: Fractal Organizations Part I – Complexity

Complex Systems Are Nested (Fractal) So an economy is made up of

organisations

which are made up departments

which are made up of people

which are made up of organs

Which are made up tissues

which are made up of cells

all of which are complex adaptive systems

The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 17: Fractal Organizations Part I – Complexity

Complex Systems Are Open

Complex systems are open

systemsmdashthat is energy and

information are constantly being

imported and exported across

system boundaries

Complex systems interact with

other complex systems through

their boundaries

It is usually difficult to determine the

boundaries of a complex system

The decision is usually based on the

observerrsquos perceptive needs and

prejudices rather than any intrinsic

property of the system itself

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 18: Fractal Organizations Part I – Complexity

Complex Systems Has Dynamical Equilibrium

Dynamical open systems has a tendency

to maximize their entropy

Which causes to attain a dynamical

equilibrium

Because of this complex systems are

usually far from equilibrium

Even though there is constant change

there is also the appearance of stability

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 19: Fractal Organizations Part I – Complexity

There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole

If they could all the complexity would have to be present in that element

Yet since the complexity is created by the relationships between elements that is simply impossible

A corollary of this is that no element in the system could hope to control the system

The Parts Cannot Contain The Whole

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 20: Fractal Organizations Part I – Complexity

Relationships Contain Nonlinear Feedback Loops

Both negative (damping) and positive

(amplifying) feedback are key ingredients of

complex systems

The effects of an agentrsquos actions are fed back to

the agent and this in turn affects the way the

agent behaves in the future

There are rarely simple cause and effect

relationships between elements

This set of constantly adapting nonlinear

relationships lies at the heart of what makes a

complex system special

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 21: Fractal Organizations Part I – Complexity

Relationships Are Short-Range

Typically the relationships between elements in a complex system are

short-range

information is normally received from near neighbours

The richness of the connections means that communications will pass

across the system but will probably be modified on the way

Contemporary information techniques overcome most of the

information barriers and deformations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 22: Fractal Organizations Part I – Complexity

Complex Systems Have A History

The history of a complex system is important

and cannot be ignored

Even a small change in circumstances can

lead to large deviations in the future

That means TIME is a fundamental

component of a Complex System

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 23: Fractal Organizations Part I – Complexity

Emergence

What distinguishes a complex

system from a merely

complicated one is that some

behaviours and patterns emerge

in complex systems as a result

of the patterns of relationship

between the elements

Emergence is perhaps the key

property of complex systems

and a lot of work is being done

to try to understand more about

its nature and the conditions

which will help it to occur

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 24: Fractal Organizations Part I – Complexity

There are many who would argue that

complexity is not just a metaphor for

organisations it is an adequate and

accurate description of organisations

It is to assert that an organisation is

more or less appropriately described in

terms of the insights being developed

by complexity theorists

However it must be recognised that

complexity theory is at present still very

tentative and undeveloped especially

in the field of human organisations

To speak of an organisation as a complex system is to adopt a theoretical stance

In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Are organisations complex adaptive systems

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 25: Fractal Organizations Part I – Complexity

Implications of Complexity Theory For Organisations

There are a number of implications which

complexity theory may potentially have

for organisations

We can only mention a few of them here

Inability to control

Inabilty to predict

Butterfly Effect

Edge of Chaos

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 26: Fractal Organizations Part I – Complexity

Inability to control

Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system

Mechanical metaphors still dominate most management thinking

So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo

Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole

If it can the system is not complex

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 27: Fractal Organizations Part I – Complexity

Inability to Predict

One of the features of complex systems is that they have

what is known as sensitivity to initial conditions

This means that a vanishingly small difference in the initial

conditions (whenever you choose to start) can make a

staggeringly large difference as time goes on

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 28: Fractal Organizations Part I – Complexity

Butterfly Effect

The classical formulation of this comes from meteorology

(Edward Lorenz a meteorologist was one of the first (1963)

to investigate the properties of complex systems such as

weather systems)

It states that even such a small perturbation as a butterfly

flapping its wings couldmdashbecause of the nonlinear nature of

the systemmdashlead to a tornado some months or years later

Of course the chances are that it wonrsquot the real issue is that

it is theoretically impossible to predict whether or not it will

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 29: Fractal Organizations Part I – Complexity

Threshold of Change For Organizations

This concept may help to deal with a key question in organisation development

ldquohow can we know if an organisation is ready to changerdquo

The answer is that we cannot know (though intuition may often be a reliable

guide) but there are some key variables which have a significant effect on

readiness and ability to change

If there is too much stability in the system change is unlikely

if there is too much randomness the system will not be able to form any

coherent patterns

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 30: Fractal Organizations Part I – Complexity

Edge of chaos

Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again

The region where changes occurred he called the edge of chaos

A key concept in much writing about complexity and organisations is the edge of chaos

It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems

The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 31: Fractal Organizations Part I – Complexity

Connectivity Diversity and Information Flow

Kaufmann and other researchers (see eg Kauffman 1995 Holland

1995 Bak 1997) working with computer simulations suggest that there

are three variables which are significant in moving systems to the edge

of chaos

connectivity

diversity and

information flow

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 32: Fractal Organizations Part I – Complexity

Edge of Chaos Can Work If

Basically stable systems can move towards the edge of chaos

1 if their agents become better connected

2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and

3 if the amount of information transferred is increased

Conversely an unstable system one with too much randomness needs to reduce some or all of these variables

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 33: Fractal Organizations Part I – Complexity

Management as Optimum Control

Similarly if there is too much control in the form of high power differentials

between different parts of the organisation creativity and readiness for change

are likely to be stifled

Contrariwise if the control mechanisms are too weak the system can dissolve

into chaotic or random behaviour

Than managament becomes a problem of ldquoOptimum Controlrdquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 34: Fractal Organizations Part I – Complexity

Self-Organisation amp Emergence

Perhaps the most interesting aspect of complex systems is their

ability to self-organise for ordered patterns to emerge simply as a

result of the relationships and interactions of the constituent

agents without any external control or design

When a complex system is at the edge of chaos it is in a state

where change may occur easily and spontaneously

When an organisation is poised at the edge of chaos even a small

stimulus may cause major change to ripple through like some

kind of domino effect

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 35: Fractal Organizations Part I – Complexity

Ability To Influence By Attractors

Another way of looking at emergence is to think about the dynamics of a complex system

If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way

These configurations are sometimes known as attractors

There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour

So we could say that a complex system will self-organise onto an attractor

It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable

The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 36: Fractal Organizations Part I – Complexity

Habitat Effect Co-Evolution

Because the environment of a CAS is made up of

other CASs all competing for resources the dynamic

between them is constantly changing in a nonlinear

fashion

In fact both competition and co-operation are at work

simultaneously leading not just to evolution but to co-

evolution

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 37: Fractal Organizations Part I – Complexity

Habitat Effect Co-Evolution

This complex lsquochicken-egg-chickenrsquo form of co-

evolution is absolutely key for understanding

complex systems and organisational change

Companies are neither masters nor slaves of their

destinies

New competitive and collaborative strategies are

now being explored in response to these insights

(Moore 1996 Nalebuff amp Brandenburger 1996)

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 38: Fractal Organizations Part I – Complexity

FitnessAnother way of looking at this wider environment is to

consider the notion of lsquofitnessrsquo

At any given time some organisations are more successful than others they are lsquofitterrsquo than others

The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems

This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 39: Fractal Organizations Part I – Complexity

To Move In A Landscape Alters The Landscape

Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems

Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change

What we do both affects and is affected by others

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 40: Fractal Organizations Part I – Complexity

Patching

Because the only way to get to a distant

fitness peak will involve getting less fit before

getting better organisations are often

reluctant to undertake such a journey

Even those chief execs who intuitively know

what has to be done seldom have models

which will help them articulate and

communicate their vision

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 41: Fractal Organizations Part I – Complexity

Self-Optimization with Patching

Patching breaks a system into connected chunks which then try to self-optimise

So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness

The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time

But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 42: Fractal Organizations Part I – Complexity

Number of Patches are not Determined

Kauffman also found that for any given system which

he modelled that there is an optimum number of

patches to help the system move to a new fitness

peak

Unfortunately there is currently no known way to

predict that number even for a simple computer

simulation let alone a human organisation

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 43: Fractal Organizations Part I – Complexity

Complexity theory is an immature field still

developing It offers great challenge to the

organisation theorist and some tantalising

possibilities and models for the organisational

practitioner

For some it is too flaky too counter to common

sense for others it is an inexhaustible source of

stimulus and excitement

There is much more but so far is enough to develop

an Object Based Complexity Theory of

Organizations

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

CO

NC

LU

SIO

N

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 44: Fractal Organizations Part I – Complexity

ldquo21TH CENTURY WILL BE

COMPLEX SCIENCE

CENTURYrdquo

Stephen HAWKING

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 45: Fractal Organizations Part I – Complexity

kutlumerihnet

kutmerihgmailcom

fatmacinarspkgovtr

httpwwwspkgovtr

httpwwwriskonomicom

fatma_cinar_ftm

fractalorg

Riskonometri

Riskonomi

CORTEXIEN

trlinkedincompubkutlu-merih9b92125a

trlinkedincominfatmacinar

Contact

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 46: Fractal Organizations Part I – Complexity

RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of

Innovation Management Vol 5 No2 pp 149 ndash 180

Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of

Organizational Structurerdquo Jossey-Bass San Francisco

Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374

Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul

Willis R (2001) ldquoPersonal Communicationrdquo London

Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London

Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association

with the Open University

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London p 157 158 164

Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics

III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 47: Fractal Organizations Part I – Complexity

Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books

London

Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural

Selectionrdquo Scientific American 265 78-84

Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin

Yapısı Alan Yayıncılık)

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured

Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)

December 17-19 at Middle East Technical University (METU) Ankara Turkey

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014

İstanbul httpwwwtrougorgp=684

Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-

cozumcomtrgorsel-veri-analizinde-devrim-mihtml

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to

the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in

Bursa Turkey on 25-27 June 2014

Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted

to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 48: Fractal Organizations Part I – Complexity

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London

Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London

Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California

McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann

Rakotobe-Joel T eds University of Warwick UK

Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed

Understanding Business Organisations Routledge London

McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational

change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I

And Rakotobe-Joel T Eds University of Warwick UK

Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo

Human Relations 52 439-462

Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of

Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK

Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -

Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY

Page 49: Fractal Organizations Part I – Complexity

Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA

Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland

ltfmichelapedroni|bertrandmeyerginfethzchgt

Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo

Complexity and Complex Systems in Industry

Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of

Management

Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F

(1996) ldquoThe Web of Liferdquo HarperCollins London

Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco

Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York

Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)

İstanbul Tuumlrk Henkel Dergisi Yayınları

RESOURCES

FRACTAL ORGANIZATIONS Part I - COMPLEXITY